--- license: mit --- # [FIDNetV3](https://github.com/CyberAgentAILab/layout-dm/blob/main/src/trainer/trainer/fid/model.py#L123-L180) from [LayoutDM](https://github.com/CyberAgentAILab/layout-dm) ```shell from transformers import AutoModel model = AutoModel.from_pretrained("shunk031/layoutdm-fidnet-v3-publaynet", trust_remote_code=True) print(model) # LayoutDmFIDNetV3( # (emb_label): Embedding(5, 256) # (fc_bbox): Linear(in_features=4, out_features=256, bias=True) # (enc_fc_in): Linear(in_features=512, out_features=256, bias=True) # (enc_transformer): TransformerWithToken( # (core): TransformerEncoder( # (layers): ModuleList( # (0-3): 4 x TransformerEncoderLayer( # (self_attn): MultiheadAttention( # (out_proj): NonDynamicallyQuantizableLinear(in_features=256, out_features=256, bias=True) # ) # (linear1): Linear(in_features=256, out_features=128, bias=True) # (dropout): Dropout(p=0.1, inplace=False) # (linear2): Linear(in_features=128, out_features=256, bias=True) # (norm1): LayerNorm((256,), eps=1e-05, elementwise_affine=True) # (norm2): LayerNorm((256,), eps=1e-05, elementwise_affine=True) # (dropout1): Dropout(p=0.1, inplace=False) # (dropout2): Dropout(p=0.1, inplace=False) # ) # ) # ) # ) # (fc_out_disc): Linear(in_features=256, out_features=1, bias=True) # (dec_fc_in): Linear(in_features=512, out_features=256, bias=True) # (dec_transformer): TransformerEncoder( # (layers): ModuleList( # (0-3): 4 x TransformerEncoderLayer( # (self_attn): MultiheadAttention( # (out_proj): NonDynamicallyQuantizableLinear(in_features=256, out_features=256, bias=True) # ) # (linear1): Linear(in_features=256, out_features=128, bias=True) # (dropout): Dropout(p=0.1, inplace=False) # (linear2): Linear(in_features=128, out_features=256, bias=True) # (norm1): LayerNorm((256,), eps=1e-05, elementwise_affine=True) # (norm2): LayerNorm((256,), eps=1e-05, elementwise_affine=True) # (dropout1): Dropout(p=0.1, inplace=False) # (dropout2): Dropout(p=0.1, inplace=False) # ) # ) # ) # (fc_out_cls): Linear(in_features=256, out_features=5, bias=True) # (fc_out_bbox): Linear(in_features=256, out_features=4, bias=True) # ) ```